Recommender systems are a well-discussed topic because of their broad application and the necessity to keep up with increasing information. While Bobadilla et al. [1]} provides an overview of the general field, Beel et al. [2]} focus specifically on research-paper. Recommender systems use data analysis techniques to help users find the content of individual relevance. These recommender systems are often categorized into three overarching approaches based on the information source utilized to generate recommendations of, namely: Content-based recommendation, collaborative recommendation, and hybrid approaches. Content-based recommender systems primarily source the available metadata of items for recommendation. In contrast, the collaborative approaches recommend items based on user interactions with items. In conjunction of both worlds, the hybrid approaches combine collaborative, and content-based methods [3]}.
